This is a momentum-based breakout trading strategy. It uses moving averages, ATR, RSI and other indicators to judge market trends and volatility, combined with strict stop loss/take profit settings for trading. The strategy mainly judges whether prices break through or fall below the moving averages plus the ATR range to generate trading signals.
The main points of this strategy are:
Use EMA to judge the price trend direction. Price crossing above EMA is bullish signal and crossing below is bearish signal.
ATR indicates market volatility. ATR multiplied by a coefficient serves as the stop loss range. This can effectively control single loss.
RSI indicates overbought/oversold status. Breakout trades signaled by stop loss price and EMA crossover must happen when RSI is not in overbought/oversold zone. This avoids false breakout.
Use previous period high/low points as take profit basis. Tracking take profit price can lock in more profits.
Strict stop loss/take profit rules. ATR-based stop loss controls risks and take profit locks in gains.
Entry signal triggers when price breaks out of EMA plus ATR stop loss range. For bullish signals, price needs to cross above the high point. For bearish signals, price needs to break below the low point.
Advantages of this strategy:
Multiple indicators avoid false breaks and improve accuracy
ATR stop loss keeps losses at reasonable level
Dynamic take profit tracking maximizes profits
Strict rules facilitate risk control
Large optimization space for indicators and parameters to adapt to different markets
Risks of this strategy:
Profitability correlates with market volatility. Gains could be limited if trend is unclear or cycle is long.
Stop loss price may whipsaw before breaking out again. This leads to missing trends. Can relax stop loss price a bit.
3.There is potential for chasing in trending markets.
Optimization ideas:
Adjust MA, ATR parameters for different products and timeframes.
Add more indicators like MACD, KDJ for overbought/oversold.
Dynamically adjust ATR coefficient based on real-time ATR values for adaptive stops.
Establish combo systems with multiple timeframes. Different timeframe indicators can improve signal quality.
Utilize machine learning for parameters/indicators optimization to achieve best performance.
This strategy utilizes indicators for judgment and strict stop loss/take profit. It takes advantage of moving averages, ATR and RSI to determine market trends. With strict risk control, it can ride trends while managing risks. Further parameter and rules optimization can make it a long-term profitable trading system.
/*backtest start: 2024-01-27 00:00:00 end: 2024-02-03 00:00:00 period: 5m basePeriod: 1m exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=4 strategy(title="UT Bot Strategy", overlay = true) //CREDITS to HPotter for the orginal code. The guy trying to sell this as his own is a scammer lol. // Inputs emaLengh = input(2, title = "emaLengh") a = input(3.0, title = "Key Vaule. 'This changes the sensitivity'") c = input(10, title = "ATR Period") h = input(false, title = "Signals from Heikin Ashi Candles") emaLengh2 = input(9, title = "emaLengh show") rate = input(0.00025, title = "波动率min") rateMax = input(0.00045, title = "波动率max") adx_length = input(20, title = "adx_length") adx_min = input(14, title = "adx_min") sma_length = input(11, title = "sma_length") rsi_len = input(9, title = "rsi_len") src = h ? security(heikinashi(syminfo.tickerid), timeframe.period, close, lookahead = false) : close // boll 通道---------------------------------------------------- length = input(20, minval=1) mult = input(2.0, minval=0.001, maxval=50, title="StdDev") basis = sma(src, length) dev = mult * stdev(src, length) upper = basis + dev lower = basis - dev bbr = (src - lower)/(upper - lower) // plot(upper, color = color.rgb(46, 59, 240), title="upper") // plot(lower, color = color.rgb(46, 59, 240), title="lower") // plot(bbr, "Bollinger Bands %B", color=#26A69A) // band1 = hline(1, "Overbought", color=#787B86, linestyle=hline.style_dashed) // hline(0.5, "Middle Band", color=color.new(#787B86, 50)) // band0 = hline(0, "Oversold", color=#787B86, linestyle=hline.style_dashed) // fill(band1, band0, color=color.rgb(38, 166, 154, 90), title="Background") // boll 通道---------------------------------------------------- // 线性回归 -------------------------------------------------------------- zlsma_length = input(title="zlsma-Length", type=input.integer, defval=50) zlsma_offset = input(title="zlsma-Offset", type=input.integer, defval=0) lsma = linreg(src, zlsma_length, zlsma_offset) lsma2 = linreg(lsma, zlsma_length, zlsma_offset) eq= lsma-lsma2 zlsma = lsma+eq // plot(zlsma , color = color.rgb(243, 243, 14), title="zlsma",linewidth=3) // 线性回归 -------------------------------------------------------------- // -------------------------------- rsi = rsi(src, 6) // xHH = sma(high, sma_length) // xLL = sma(low, sma_length) // movevalue = (xHH - xLL) / 2 // xHHM = xHH + movevalue // xLLM = xLL - movevalue // plot(xHHM, color = color.rgb(208, 120, 219), title="xHHM") // plot(xLLM, color = color.rgb(208, 120, 219), title="xLLM") xATR = atr(c) nLoss = a * xATR xATRTrailingStop = 0.0 xATRTrailingStop := iff(src > nz(xATRTrailingStop[1], 0) and src[1] > nz(xATRTrailingStop[1], 0), max(nz(xATRTrailingStop[1]), src - nLoss), iff(src < nz(xATRTrailingStop[1], 0) and src[1] < nz(xATRTrailingStop[1], 0), min(nz(xATRTrailingStop[1]), src + nLoss), iff(src > nz(xATRTrailingStop[1], 0), src - nLoss, src + nLoss))) pos = 0 pos := iff(src[1] < nz(xATRTrailingStop[1], 0) and src > nz(xATRTrailingStop[1], 0), 1, iff(src[1] > nz(xATRTrailingStop[1], 0) and src < nz(xATRTrailingStop[1], 0), -1, nz(pos[1], 0))) xcolor = pos == -1 ? color.red: pos == 1 ? color.green : color.blue ema = ema(src,emaLengh) // sma = sma(src,emaLengh) emaFast = ema(src,100) emaSlow = ema(src,576) emaShow = ema(src, emaLengh2) // sma = sma(src, 8) // [superTrend, dir] = supertrend(3, 200) // 判断连续涨 [diplus, diminus, adx] = dmi(adx_length, adx_length) above = crossover(ema, xATRTrailingStop) below = crossover(xATRTrailingStop, ema) // above = ema == xATRTrailingStop // below = xATRTrailingStop== ema // smaabove = crossover(src, sma) // smabelow = crossover(sma, src) // smaabove = src > sma // smabelow = sma > src close_rate (n)=> abs(close[n]-open[n])/min(close[n],open[n]) rate_val = close_rate(0) rate_val1 = close_rate(1) buy = src > xATRTrailingStop and above and src > zlsma and adx >adx_min // and src>emaShow // and rate_val < rate_val1*2 and rate_val >=rate_val1 // and rate_val1<rateMax // and close[1]>open[1] sell = src < xATRTrailingStop and below and src < zlsma and adx >adx_min // and src<emaShow // and rate_val < rate_val1*2 and rate_val >=rate_val1 // and rate_val1<rateMax // and open[1]>close[1] and rate_val1 > rate // buy = src > xATRTrailingStop // sell = src < xATRTrailingStop // plot(rate_val1 , color = color.red, title="rate_val1") barbuy = src > xATRTrailingStop barsell = src < xATRTrailingStop atrRsi = rsi(xATRTrailingStop,rsi_len) // plot(emaFast , color = color.rgb(243, 206, 127), title="emaFast") // plot(ema , color = color.rgb(47, 227, 27), title="ut-ema") // plot(emaShow , color = color.rgb(47, 227, 27), title="ema9") plot(xATRTrailingStop, color = color.rgb(233, 233, 232), title="xATRTrailingStop") plotshape(buy, title = "Buy", text = 'Buy', style = shape.labelup, location = location.belowbar, color= color.green, textcolor = color.white, size = size.tiny) plotshape(sell, title = "Sell", text = 'Sell', style = shape.labeldown, location = location.abovebar, color= color.red, textcolor = color.white, size = size.tiny) // plotshape(buy, title = "Sell", text = 'Sell', style = shape.labelup, location = location.belowbar, color= color.green, textcolor = color.white, transp = 0, size = size.tiny) // plotshape(sell, title = "buy", text = 'buy', style = shape.labeldown, location = location.abovebar, color= color.red, textcolor = color.white, transp = 0, size = size.tiny) // barcolor(barbuy ? color.green : na) // barcolor(barsell ? color.red : na) // strategy.entry("short", false, when = buy) // strategy.entry("long ", true, when = sell) strategy.entry("long", true, when = buy and strategy.position_size == 0) strategy.entry("short", false, when = sell and strategy.position_size == 0) //动态止盈start------------------------------------------------------------------------------------------ profit = input( 0.015, title = "最小收益率") close_profit_rate = input( 10, title = "平仓收益回撤比") loss = input(0.004, title = "回撤率") // 收益回撤比例 profit_price_scale =profit/close_profit_rate var float profit_price = 0 // 计算小收益价格 get_profit_price(long) => float res = 0 if long == true res := strategy.position_avg_price * (1+profit) if long == false res := strategy.position_avg_price * (1-profit) res // 止盈平仓条件 close_profit_position(long)=> bool result=false if long == true and profit_price>0 and profit_price*(1-profit_price_scale) >=close and get_profit_price(true) <= close result:=true if long == false and profit_price>0 and profit_price*(1+profit_price_scale) <=close and get_profit_price(false) >= close result:=true result // 更新动态止盈价格 update_profit_price(price)=> float res = price // 无仓位时 动态止盈价格为0 if strategy.position_size == 0 res := 0 // long - 价格大于最小收益时保存 if strategy.position_size > 0 and get_profit_price(true) <= close and (res==0 or res < close) res := close // short - 价格小于最小收益时保存 if strategy.position_size < 0 and get_profit_price(true) >= close and (res==0 or res > close) res := close res /////// profit_price := update_profit_price(profit_price) long_close_profit_position = close_profit_position(true) short_close_profit_position = close_profit_position(false) // plot(profit_price, color = color.green, title="profit_price") //动态止盈end------------------------------------------------------------------------------------------ strategy.close("long",comment="long-止盈",when = strategy.position_size > 0 and long_close_profit_position) strategy.close("long",comment="long-止损",when = strategy.position_size >0 and strategy.position_avg_price * (1-loss) >= close) strategy.close("short",comment="short-止盈",when = strategy.position_size <0 and short_close_profit_position) strategy.close("short",comment="short-止损",when = strategy.position_size <0 and strategy.position_avg_price * (1+loss) <= close)template: strategy.tpl:40:21: executing "strategy.tpl" at <.api.GetStrategyListByName>: wrong number of args for GetStrategyListByName: want 7 got 6